DATA MANAGEMENT PROFESSIONAL CERTIFICATION
Building Foundational Expertise in Data Governance, Quality, Integration, and Lifecycle Management
Course Schedule
| Date | Venue | Fees |
|---|---|---|
| 27 – 28 Feb 2025 | Online (Live Virtual) | USD 700 per delegate |
Course Introduction
In the digital economy, data is a core organizational asset—but only when managed effectively. Poor data quality, fragmented systems, and lack of governance can lead to costly errors, compliance issues, and missed opportunities. This course provides professionals with a practical and foundational understanding of data management principles aligned with global standards such as DAMA-DMBOK.
Delivered online in an interactive format, this two-day certification program equips participants with the tools and frameworks to support data strategy, governance, stewardship, integration, and lifecycle management in any organization or industry.
Course Objectives
By the end of this course, participants will be able to:
• Understand the core components of enterprise data management
• Apply best practices in data governance, quality, and security
• Recognize key roles and responsibilities in a data-driven organization
• Implement practical frameworks for data lifecycle and metadata management
• Prepare for industry-recognized certification in data management
Key Benefits of Attending
• Build a solid foundation in data management aligned with global frameworks (DAMA-DMBOK)
• Improve your ability to organize, protect, and leverage data assets
• Gain tools to contribute to data governance and data quality initiatives
• Increase your value as a data-aware professional in any functional role
• Prepare to advance toward CDMP or other professional data certifications
Intended Audience
This program is designed for:
• Data analysts, stewards, and governance professionals
• IT managers, business analysts, and project leads
• Professionals working with enterprise systems or reporting tools
• Data owners and custodians in operations, finance, marketing, or compliance
• Anyone seeking to formalize or grow their data management expertise
Individual Benefits
Key competencies that will be developed include:
• Understanding of key data management domains and practices
• Ability to contribute to governance, quality, and integration projects
• Awareness of data roles, responsibilities, and standards
• Knowledge of tools and techniques to manage data across its lifecycle
• Certification readiness in professional data management disciplines
Organization Benefits
Upon completing the training course, participants will demonstrate:
• More consistent and reliable data for decision-making and reporting
• Increased awareness of compliance, privacy, and data protection risks
• Better coordination of data ownership and accountability
• Improved project outcomes through structured data management
• Enhanced readiness for digital transformation and analytics initiatives
Instructional Methdology
The course follows a blended virtual learning approach combining theory with live engagement:
• Strategy Briefings – Overview of data management functions and frameworks (e.g., DAMA-DMBOK)
• Case Studies – Examples of successful and failed data governance projects
• Workshops – Hands-on sessions to apply data lifecycle, quality, and governance models
• Peer Exchange – Breakout discussions and experience sharing across roles and sectors
• Tools – Sample data policies, quality metrics templates, and governance role maps
Course Outline
DETAILED 2-DAY COURSE OUTLINE
Delivery Format: Online (Live)
Platform: Zoom, WebEx or Microsoft Teams
Training Hours: 7:30 AM – 3:30 PM (with scheduled virtual breaks)
Day 1: Foundations of Enterprise Data Management
Module 1: Introduction to Data Management and DAMA Framework (07:30 – 09:30)
• Key drivers for data management
• Overview of DAMA-DMBOK knowledge areas
• Data management maturity models
Module 2: Data Governance and Organizational Roles (09:45 – 11:15)
• Policies, standards, and governance councils
• Roles: owner, steward, custodian, user
• Governance structure and escalation paths
Module 3: Data Quality Management (11:30 – 01:00)
• Dimensions of data quality: accuracy, completeness, consistency, timeliness
• Data profiling and root cause analysis
• Quality rules, metrics, and monitoring
Module 4: Workshop – Governance & Quality Diagnostics (02:00 – 03:30)
• Group work on assessing governance maturity and data quality risks
Day 2: Data Integration, Lifecycle, and Certification Preparation
Module 1: Data Integration and Interoperability (07:30 – 09:30)
• ETL, APIs, data pipelines, and master data
• Avoiding silos and fragmentation
• Supporting analytics and reporting
Module 2: Metadata and Reference Data Management (09:45 – 11:15)
• Types of metadata and their uses
• Reference vs. master data
• Metadata repositories and data catalogs
Module 3: Data Lifecycle and Security (11:30 – 01:00)
• From data creation to archival/disposal
• Privacy, protection, and classification of data
• Data retention and compliance
Module 4: Final Workshop – Data Management Readiness Plan (02:00 – 03:30)
• Develop a 60-day plan to support data management at work
• Certification pathways and knowledge review
• Course wrap-up and Q&A
Certification
Participants will receive a Certificate of Completion in Data Management Professional Certification, validating their understanding of data governance, quality, integration, and lifecycle management best practices aligned with international standards.